Akira Maruoka

According to our database, Akira Maruoka authored at least 72 papers between 1973 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2020

Analyzing trajectories of learning processes through behaviour-based entropy.

Shinsuke Seino, Kenji Kimura, Satoshi Kawamura, Yoshifumi Sasaki, Akira Maruoka

J. Exp. Theor. Artif. Intell., 2020

2019

The Upper Bound on the Eulerian Recurrent Lengths of Complete Graphs Obtained by an IP Solver.

Shuji Jimbo, Akira Maruoka

Proceedings of the WALCOM: Algorithms and Computation - 13th International Conference, 2019

Halide and GENESIS for Generating Domain-Specific Architecture of Guided Image Filtering.

Akari Ishikawa, Norishige Fukushima, Akira Maruoka, Takuro Iizuka

Proceedings of the IEEE International Symposium on Circuits and Systems, 2019

2013

A Maximum Matching Based Heuristic Algorithm for Partial Latin Square Extension Problem.

Kazuya Haraguchi, Masaki Ishigaki, Akira Maruoka

Proceedings of the 2013 Federated Conference on Computer Science and Information Systems, 2013

2012

How to Produce BlockSum Instances with Various Levels of Difficulty.

Kazuya Haraguchi, Yasutaka Abe, Akira Maruoka

J. Inf. Process., 2012

2008

Monotone DNF Formula That Has a Minimal or Maximal Number of Satisfying Assignments.

Takayuki Sato, Kazuyuki Amano, Eiji Takimoto, Akira Maruoka

Proceedings of the Computing and Combinatorics, 14th Annual International Conference, 2008

2007

Better upper bounds on the QOBDD size of integer multiplication.

Kazuyuki Amano, Akira Maruoka

Discret. Appl. Math., 2007

2006

On learning monotone Boolean functions under the uniform distribution.

Kazuyuki Amano, Akira Maruoka

Theor. Comput. Sci., 2006

Online Allocation with Risk Information.

Shigeaki Harada, Eiji Takimoto, Akira Maruoka

IEICE Trans. Inf. Syst., 2006

The Monotone Circuit Complexity of Quadratic Boolean Functions.

Kazuyuki Amano, Akira Maruoka

Algorithmica, 2006

On the Negation-Limited Circuit Complexity of Sorting and Inverting <i>k</i>-tonic Sequences.

Takayuki Sato, Kazuyuki Amano, Akira Maruoka

Proceedings of the Computing and Combinatorics, 12th Annual International Conference, 2006

Aggregating Strategy for Online Auctions.

Shigeaki Harada, Eiji Takimoto, Akira Maruoka

Proceedings of the Computing and Combinatorics, 12th Annual International Conference, 2006

2005

A Superpolynomial Lower Bound for a Circuit Computing the Clique Function with at most (1/6)log log <i>n</i> Negation Gates.

Kazuyuki Amano, Akira Maruoka

SIAM J. Comput., 2005

On the Complexity of Depth-2 Circuits with Threshold Gates.

Kazuyuki Amano, Akira Maruoka

Proceedings of the Mathematical Foundations of Computer Science 2005, 2005

2004

The Potential of the Approximation Method.

Kazuyuki Amano, Akira Maruoka

SIAM J. Comput., 2004

Relationships between Horn Formulas and XOR-MDNF Formulas.

Kenshi Matsuo, Tetsuya Koyama, Eiji Takimoto, Akira Maruoka

IEICE Trans. Inf. Syst., 2004

Better Simulation of Exponential Threshold Weights by Polynomial Weights

Kazuyuki Amano, Akira Maruoka

Electron. Colloquium Comput. Complex., 2004

Boosting Based on Divide and Merge.

Eiji Takimoto, Syuhei Koya, Akira Maruoka

Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2003

Top-down decision tree learning as information based boosting.

Eiji Takimoto, Akira Maruoka

Theor. Comput. Sci., 2003

Inclusion-exclusion for k-CNF formulas.

Kazuyuki Amano, Kazuo Iwama, Akira Maruoka, Kenshi Matsuo, Akihiro Matsuura

Inf. Process. Lett., 2003

On the negation-limited circuit complexity of merging.

Kazuyuki Amano, Akira Maruoka, Jun Tarui

Discret. Appl. Math., 2003

On Optimal Merging Networks.

Kazuyuki Amano, Akira Maruoka

Proceedings of the Mathematical Foundations of Computer Science 2003, 2003

Some Properties of MOD_m Circuits Computing Simple Functions.

Kazuyuki Amano, Akira Maruoka

Proceedings of the Algorithms and Complexity, 5th Italian Conference, 2003

2002

Top-Down Decision Tree Boosting and Its Applications.

Eiji Takimoto, Akira Maruoka

Proceedings of the Progress in Discovery Science, 2002

On-Line Algorithm to Predict Nearly as Well as the Best Pruning of a Decision Tree.

Akira Maruoka, Eiji Takimoto

Proceedings of the Progress in Discovery Science, 2002

2001

Predicting nearly as well as the best pruning of a decision tree through dynamic programming scheme.

Eiji Takimoto, Akira Maruoka, Volodya Vovk

Theor. Comput. Sci., 2001

The Computational Power of a Family of Decision Forests.

Kazuyuki Amano, Tsukuru Hirosawa, Yusuke Watanabe, Akira Maruoka

Proceedings of the Mathematical Foundations of Computer Science 2001, 2001

2000

The learnability of exclusive-or expansions based on monotone DNF formulas.

Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka

Theor. Comput. Sci., 2000

Learning Monotone Log-Term DNF Formulas under the Uniform Distribution.

Yoshifumi Sakai, Akira Maruoka

Theory Comput. Syst., 2000

On-Line Estimation of Hidden Markov Model Parameters.

Jun Mizuno, Tasuya Watanabe, Kazuya Ueki, Kazuyuki Amano, Eiji Takimoto, Akira Maruoka

Proceedings of the Discovery Science, 2000

1999

Proper Learning Algorithm for Functions of k Terms under Smooth Distributions.

Yoshifumi Sakai, Eiji Takimoto, Akira Maruoka

Inf. Comput., 1999

1998

Consistency of Natural Relations on Sets.

Akira Maruoka, Mike Paterson, Hirotaka Koizumi

Comb. Probab. Comput., 1998

On the Boosting Algorithm for Multiclass Functions Based on Information-Theoretic Criterion for Approxiamtion.

Eiji Takimoto, Akira Maruoka

Proceedings of the Discovery Science, 1998

Structured Weight-Based Prediction Algorithms.

Akira Maruoka, Eiji Takimoto

Proceedings of the Algorithmic Learning Theory, 9th International Conference, 1998

1997

Learning Orthogonal F-Horn Formulas.

Eiji Takimoto, Akira Miyashiro, Akira Maruoka, Yoshifumi Sakai

Theor. Comput. Sci., 1997

Approximation Algorithms for DNF Under Distributions with Limited Independence.

Kazuyuki Amano, Akira Maruoka

Theory Comput. Syst., 1997

A Simple Algorithm for Predicting Nearly as Well as the Best Pruning Labeled with the Best Prediction Values of a Decision Tree.

Eiji Takimoto, Ken'ichi Hirai, Akira Maruoka

Proceedings of the Algorithmic Learning Theory, 8th International Conference, 1997

1996

A Method of Constructing Selection Networks with O(log n) Depth.

Shuji Jimbo, Akira Maruoka

SIAM J. Comput., 1996

Approximation of the size of the union.

Shuji Jimbo, Akira Maruoka

Syst. Comput. Jpn., 1996

Potential of the Approximation Method (extended abstract).

Kazuyuki Amano, Akira Maruoka

Proceedings of the 37th Annual Symposium on Foundations of Computer Science, 1996

Learnability of Exclusive-Or Expansion Based on Monotone DNF Formulas.

Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka

Proceedings of the Algorithmic Learning Theory, 7th International Workshop, 1996

1995

Loop Circuits and Their Relation to Razborov's Approximation Model

Katsutoshi Nakayama, Akira Maruoka

Inf. Comput., June, 1995

On the Sample Complexity of Consistent Learning with One-Sided Error.

Eiji Takimoto, Akira Maruoka

IEICE Trans. Inf. Syst., 1995

Proper Learning Algorithm for Functions of <i>k</i> Terms Under Smooth Distributions.

Yoshifumi Sakai, Eiji Takimoto, Akira Maruoka

Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

Learning Orthogonal <i>F</i>-Horn Formulas.

Akira Miyashiro, Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka

Proceedings of the Algorithmic Learning Theory, 6th International Conference, 1995

1994

Construction of pseudorandom permutations.

Yasuhiro Ohnishi, Akira Maruoka

Syst. Comput. Jpn., 1994

On the Relationship Between varepsilon-Biased Random Variables and varepsilon-Dependent Random Variables.

Shuji Jimbo, Akira Maruoka

Inf. Process. Lett., 1994

On the Relationship Between the Diameter and the Size of a Boundary of a Directed Graph.

Shuji Jimbo, Akira Maruoka

Inf. Process. Lett., 1994

Learning Monotone Log-Term DNF Formulas.

Yoshifumi Sakai, Akira Maruoka

Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, 1994

Mutual Information Gaining Algorithm and Its Relation to PAC-Learning Algorithm.

Eiji Takimoto, Ichiro Tajika, Akira Maruoka

Proceedings of the Algorithmic Learning Theory, 1994

1993

Relationships between learning and information compression based on PAC learning model.

Eiji Takimoto, Akira Maruoka

Syst. Comput. Jpn., 1993

Conservativeness and Monotonicity for Learning Algorithms.

Eiji Takimoto, Akira Maruoka

Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

1992

Learning Monotone Boolean Functions by Uniformly Distributed Examples.

Qian-Ping Gu, Akira Maruoka

SIAM J. Comput., 1992

Selection Networks with 8<i>n</i> log₂<i>n</i> Size and <i>O</i>(log <i>n</i>) Depth.

Shuji Jimbo, Akira Maruoka

Proceedings of the Algorithms and Computation, Third International Symposium, 1992

Learning <i>k</i>-Term Monotone Boolean Formulae.

Yoshifumi Sakai, Akira Maruoka

Proceedings of the Algorithmic Learning Theory, Third Workshop, 1992

1991

Amplification of Bounded Depth Monotone Read-Once Boolean Formulae.

Qian-Ping Gu, Akira Maruoka

SIAM J. Comput., 1991

Learning boolean functions.

Qian-Ping Gu, Akira Maruoka

Syst. Comput. Jpn., 1991

Relationships between PAC-learning algorithms and weak Occam algorithms.

Eiji Takimoto, Akira Maruoka

Proceedings of the Algorithmic Learning Theory, 2nd International Workshop, 1991

1987

Expanders obtained from affine transformations.

Shuji Jimbo, Akira Maruoka

Comb., 1987

1986

Complexity Based on Partitioning of Boolean Circuits and Their Relation to Multivalued Circuits.

Akira Maruoka

IEEE Trans. Computers, 1986

Time and communication complexity in parallel computations.

Hiroshi Ishioka, Akira Maruoka, Masayuki Kimura

Syst. Comput. Jpn., 1986

1985

Expanders Obtained from Affine Transformations (Preliminary Version)

Shuji Jimbo, Akira Maruoka

Proceedings of the 17th Annual ACM Symposium on Theory of Computing, 1985

1983

Open Maps for Tessellation Automata.

Akira Maruoka

Theor. Comput. Sci., 1983

1982

Strong Surjectivity is Equivalent to C-Injectivity.

Akira Maruoka, Masayuki Kimura

Theor. Comput. Sci., 1982

1981

Pattern Decomposition for Tessellation Automata.

Akira Maruoka, Masayuki Kimura, Nobuyoshi Shoji

Theor. Comput. Sci., 1981

1979

Injectivity and Surjectivity of Parallel Maps for Cellular Automata.

Akira Maruoka, Masayuki Kimura

J. Comput. Syst. Sci., 1979

1977

Completeness Problem of Multidimensional Tessellation Automata

Akira Maruoka, Masayuki Kimura

Inf. Control., September, 1977

Decomposition Phenomenon in One-Dimensional Scope-Three Tessellation Automata with Arbitrary Number of States

Akira Maruoka, Masayuki Kimura

Inf. Control., August, 1977

1976

Condition for Injectivity of Global Maps for Tessellation Automata

Akira Maruoka, Masayuki Kimura

Inf. Control., October, 1976

1975

The Range of Logical Flexibility of Tree Networks.

Akira Maruoka, Namio Honda

IEEE Trans. Computers, 1975

1974

Completeness Problem of One-Dimensional Binary Scope-3 Tessellation Automata.

Akira Maruoka, Masayuki Kimura

J. Comput. Syst. Sci., 1974

1973

Logical Networks of Flexible Cells.

Akira Maruoka, Namio Honda

IEEE Trans. Computers, 1973